Connecting electronic portfolios and learner models

Using electronic portfolios (e-portfolios) to assist learning is an important component of future educational models. A portfolio is a purposeful collection of student work that exhibits the student's efforts, progress and achievements in one or more areas. An e-portfolio contains a variety of information about a person's learning outcomes, such as artifacts, assertions from others, self-reflective information and presentation for different purposes. E-portfolios become sources of evidence for claims about prior conceptual knowledge or skills. This thesis investigates using the information contained in e-portfolios to initialize the learner model for an intelligent tutoring system. We examine the information model from the e-portfolio standardized specification and present a method that may assist users in initializing learner models using e-portfolios as evidence for claims about prior conceptual knowledge or skills. We developed the EP-LM system for testing how accurately a learner model can be built and how beneficial this approach can be for reflective and personalized learning. Experimental results are presented aiming at testing whether accurate learner models can be created through this approach and whether learners can gain benefits in reflective and personalized learning. Monitoring this process can also help ITS developers and experts identify how an initial learner model can automatically arise from an e-portfolio. Additionally, a well-structured learner model, generated by an intelligent tutoring system also can be attached to an e-portfolio for further use by the owner and others

Predicting corporate bond returns in the US bond market via machine learning

We perform a comparative analysis of two machine learning methods to predict corporate bond return in the US bond market. In contrast to previous studies, we find that the most influential variables are associated with size risk and past return. However, credit and liquidity risks are more prominent when negative externalities impact the market. Further, high predictability at short horizons combined with the investment strategy employed translates into highly significant alphas. We identify the best-performing method to be a decisiontree- based model utilizing boosting. The out-of-sample performance for this method remains statistically significant after accounting for transaction costs.nhhma

Wiley Interdiscip Rev Comput Stat

Forecasts support decision making in a variety of applications. Statistical models can produce accurate forecasts given abundant training data, but when data is sparse or rapidly changing, statistical models may not be able to make accurate predictions. Expert judgmental forecasts-models that combine expert-generated predictions into a single forecast-can make predictions when training data is limited by relying on human intuition. Researchers have proposed a wide array of algorithms to combine expert predictions into a single forecast, but there is no consensus on an optimal aggregation model. This review surveyed recent literature on aggregating expert-elicited predictions. We gathered common terminology, aggregation methods, and forecasting performance metrics, and offer guidance to strengthen future work that is growing at an accelerated pace.R35 GM119582/GM/NIGMS NIH HHSUnited States/U01 IP001122/IP/NCIRD CDC HHSUnited States/2022-03-01T00:00:00Z33777310PMC799632111017vault:3684

English Language Teacher Self-Efficacy Beliefs

This dissertation investigates English language teacher self-efficacy beliefs. Based in Bandura’s (1997) sociocognitive perspective, teachers’ self-efficacy beliefs, their beliefs about their capabilities to enact various teaching tasks, have been shown to be impactful on numerous aspects of teachers’ professional lives. Research in both general education and language teacher education has shown that more efficacious teachers are often more motivated, exert a greater effort when teaching, have a higher morale, and can even positively impact their students. Drawing on survey data from N = 571 participants across a variety of English language teaching contexts, this thesis takes an integrated article format and addresses unresolved issues in English language teacher self-efficacy research. Chapters 1 and 2 outline the thesis and provide background literature and the thesis’ theoretical perspective. Chapter 3 consists of the first research portion of this thesis and outlines the creation of a new English language teacher self-efficacy scale. Initial items are drawn from various TESOL (Teaching English to Speakers of Other Languages) standards documents and then subjected to exploratory factor analysis. The final scale, consisting of 26 items across 6 unique factors, serves as the research instrument for the remainder of the dissertation. Chapter 4 investigates the self-efficacy beliefs of English language teachers in North America (Canada and the United States). It looks at what their levels of self-efficacy are, and also if/how teachers’ classroom proficiency, general language proficiency, experience, language teacher education (LTE) qualifications, and linguistic identity impact this self-efficacy. Utilizing a series of simultaneous multiple regression analyses, results show that teachers’ classroom proficiency is the most significant predictor of teachers’ self-efficacy, but general English proficiency, teaching experience and linguistic identity are also significantly impactful as well. Chapter 5 takes a similar methodological approach and investigates the self-efficacy beliefs of non-native English speaking teachers (NNESTs) across a variety of EFL contexts. The results again show the importance of teachers’ self-perceived classroom proficiency as this significantly predicted teachers’ self-efficacy across all of the factors. The dissertation ends with Chapter 6 that serves as a final discussion for the entire thesis followed by this study’s limitations and potential future directions

Razvoj Modela uspješnosti ePortfolio sustava

Electronic Portfolio constitutes an extension to e-learning and has therefore been very strongly popularized in the last few years. Since the field of ePortfolio is still unexplored, there is not a model to describe the successful implementation of an ePortfolio taking into account the individual (student, educator), academic institution, and industry (employer) level. However, research conducted so far refer to the importance of ePortfolio system and suggest the need to develop an integral model which will comprehend both the pedagogical and ICT potential of an ePortfolio system. In this doctoral dissertation, an instrument to evaluate ePortfolio success, using the DeLone&McLean updated IS success model as the assessment framework, will be developed. Based on the results of instrument developed and D&M model, an integral model of ePortfolio success will be proposed.Elektronički Portfolio ili ePortfolio predstavlja proširenje e-učenja, te se vrlo snažno popularizira u posljednjih nekoliko godina. Kako je područje još uvijek vrlo neistraženo, ne postoji model koji opisuje mogućnosti uspješne implementacije ePortfolio sustava koji bi obuhvaćao pojedinca (studenta, nastavnika), akademsku instituciju, te poslodavca (industrije). Dosadašnja istraživanja upućuju na važnost ePortfoliosustava, te sugeriraju izgradnju cjelovitog modela koji će obuhvaćati i pedagoški i ICT potencijal ePortfolio sustava. U ovoj doktorskoj disertaciji razvit de se instrument za vrednovanje uspješnosti ePortfolija korištenjem DeLone i McLean poboljšanog modela uspješnosti informacijskog sustava (u daljnjem tekstu: D&M model) kao okvira za procjenu. Na temelju rezultata razvijenog instrumenta i spomenutog D&M modela predložit će se cjeloviti model uspješnosti ePortfolio sustava

Razvoj Modela uspješnosti ePortfolio sustava

Electronic Portfolio constitutes an extension to e-learning and has therefore been very strongly popularized in the last few years. Since the field of ePortfolio is still unexplored, there is not a model to describe the successful implementation of an ePortfolio taking into account the individual (student, educator), academic institution, and industry (employer) level. However, research conducted so far refer to the importance of ePortfolio system and suggest the need to develop an integral model which will comprehend both the pedagogical and ICT potential of an ePortfolio system. In this doctoral dissertation, an instrument to evaluate ePortfolio success, using the DeLone&McLean updated IS success model as the assessment framework, will be developed. Based on the results of instrument developed and D&M model, an integral model of ePortfolio success will be proposed.Elektronički Portfolio ili ePortfolio predstavlja proširenje e-učenja, te se vrlo snažno popularizira u posljednjih nekoliko godina. Kako je područje još uvijek vrlo neistraženo, ne postoji model koji opisuje mogućnosti uspješne implementacije ePortfolio sustava koji bi obuhvaćao pojedinca (studenta, nastavnika), akademsku instituciju, te poslodavca (industrije). Dosadašnja istraživanja upućuju na važnost ePortfoliosustava, te sugeriraju izgradnju cjelovitog modela koji će obuhvaćati i pedagoški i ICT potencijal ePortfolio sustava. U ovoj doktorskoj disertaciji razvit de se instrument za vrednovanje uspješnosti ePortfolija korištenjem DeLone i McLean poboljšanog modela uspješnosti informacijskog sustava (u daljnjem tekstu: D&M model) kao okvira za procjenu. Na temelju rezultata razvijenog instrumenta i spomenutog D&M modela predložit će se cjeloviti model uspješnosti ePortfolio sustava